DESCRIPTION: Women with a high proportion of mammographically dense breast tissue have a three to six-fold increased risk of developing breast cancer. The percent of the breast that appears dense on a mammogram reflects the proportion of stromal and epithelial tissue compared to fat, and varies considerably among healthy women. In well-designed studies, the magnitude of the breast cancer risk associated with increased mammographic density exceeded that of most other predictors, and was independent of the traditional breast cancer risk factors. The proposed study will expand the current understanding of mammographic density and for the first time evaluate the associations between plasma levels of endogenous hormones, growth factors, insulin, cholesterol, nutrients and antioxidants with mammographic density and breast cancer risk. This study benefits from the prospective design and extensive information available for the subjects in the ongoing case-control study of plasma biomarkers and breast cancer risk (CA49449), nested within the Nurse's Health Study (CA40356). It is estimated that both mammographic information and plasma biomarkers will be available for 690 cases and 924 controls. Among these cases and controls this study will determine if the breast cancer risk associated with mammographic density is explained by the plasma levels of growth factors, insulin, cholesterol, nutrients and antioxidants. Among the 233 cases and 466 controls who were postmenopausal and not using postmenopausal hormones at the time of the blood donation, this study is intended to determine if the breast cancer risk associated with mammographic density is partially explained by the plasma levels of endogenous hormones. To assess mammographic density this study will employ a newly developed method, which is designed to determine the percent of the breast area with mammographic density based on a texture analysis of the digitized image, capturing the relation between stromal and epithelial tissue. As part of this study, the new computerized system to assess mammographic features will be compared to the existing techniques of assessing percent mammographic density: 1) a visual assessment of percent density by a radiologist; 2) measured assessment from the marked area of density; and 3) a computer-assisted measure of percent density from a grey-scale based system.